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Volver a Análisis de datos con Python

Opiniones y comentarios de aprendices correspondientes a Análisis de datos con Python por parte de Habilidades en redes de IBM

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Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Principales reseñas


5 de may. de 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.


19 de abr. de 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

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151 - 175 de 2,311 revisiones para Análisis de datos con Python

por Sachin B

27 de nov. de 2021

I always fascinated towards programming languages from university days as it makes the complicated work easier. as having basic cleared about python helps me to sail out through this course. all levels are thoroughly covered with proper scripts which make better understanding even for newcomers also.

por Mack S

20 de jun. de 2022

Great course with helpful excersise. The only thing that needs to be looked into is peer review for projects. One of the peers rated my project 8 out of 18 and i was asked to re do but because i knew it was correct i just resubmitted without changing anything and 3 peers who reviewed gave me 17/18

por Meenakshi S A

20 de nov. de 2019

It was a very interesting and correctly paced course for learning Data Analysis with Python. The course content and the assignments were very helpful in understanding the course well. Will recommend this course to all who want to do a well paced introductory course on Data Analytics using Python

por Md. R H

22 de sep. de 2019

This course is outstanding valuable for the beginners who wants to build their career as data analysist. I have learned a lots of valuable statistical and progrmming for data analysis. Thanks to all instructor to give us such a opportunity to learn such kind of code and method for data analysis.

por Marta F d O F d N N

2 de jun. de 2020

This was a great introductory course to statistical modeling with Python. I learned a lot of the basic methods to perform linear regression models and to describe statistical variables. The final assignment was slightly challenging, but doable if you follow the labs. All and all a great course!

por Jamiil T A

1 de ene. de 2019

Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.

por Alpesh G

11 de ago. de 2021

This course starts with Importing the dataset in Jupyter Notebook, followed by Data Wrangling, Exploratory Data Analysis, Model Development and Model Evaluation, and end with the final assessment applying all the concepts learned.

Thanks to IBM and Coursera for this great learning experience.

por Viren B

31 de may. de 2021

the course is too good to be true! it is an elaborate explanation of all the terms with the logic behind it. Seamless experience with the inbuilt code writing lab. I would highly recommend it to all who are at the doorstep of data analysis. This is the first step towards it, and a mighty one!

por Md. A A J

2 de may. de 2020

The hands on examples for practicing on IBM cognitive lab, videos and lecturers made are great and helpful. The course contents are clear, precise and lecturer is very knowledgeable.

Joining and getting help from course mates and moderates in discussion forum is Excellent!

Ashfaque A. Joarder

por Gregory J O C

27 de jun. de 2020

I loved this course!

Though, for a beginner like me, it can be kind of confusing to be shown things that are not covered in the course (i.e, plots in which a lot of characteristics have to be set...), this tends to happen in labs.

But for the rest, everything was crystal clear!

Best wishes!

por Konstantin D

22 de feb. de 2019

The first "week" was way too simple. I believe things like "what a file path is" should belong to another course. The last 4 "weeks" gave a good picture of where to start with data analysis. The whole course can be completed after 5-10 hours (depends how long you play with the dev tool).

por Sumanta S

9 de sep. de 2020

This course builds your fundamentals of data analysis ,from how to load data to data cleaning, removing missing values, data interpretation, building models, testing them using pipleine to check if model gives proper output , splitting data sets as test set and for model learning. etc

por Surhan Z

15 de jun. de 2019

This course core purpose is to teach the student how to perform analysis in detail. I have taken a lot of courses related to data analysis but no one teaches in detail and gives great examples. I highly recommend this course to all student who wants to learn data analysis with python.

por V C

15 de ene. de 2020

This course is actually harder than expected due to the python programming however I felt I truly benefited from it. I have learned and used Python before, but the python code in this course sets a new high bar for me. I'm going to go back and study all the labs in this course again!

por Aman T

19 de abr. de 2020

This was a good course. It had lot of content you will find data analysis with pandas library along with analysis there is regression machine learning model also and model evaluation section. Overall it was a great experience. Content was nice and I recommend to everyone to enroll.

por Ketan K

28 de dic. de 2018

Really a step up in terms of difficulty compared to "Data Science with Python". Since the final week's content is judged on quiz and not a stand alone assignment, one must revise this course from time to time for the libraries referenced and model analysis approach. Great resource!

por Anthony G

25 de ene. de 2021

This course was presented clearly and explained statistical concepts in a way that made them relevant and practical. The assignments were challenging, requiring review of notes and Python techniques made during the lectures, thereby reinforcing the learning outcomes in a good way.

por Gajula J

16 de jul. de 2018

This course is very good start for students who are planning to go into machine learning specifically.Students who have no Idea about regression and math find bit hard but little more effort from student side is needed. At the end you will have a zeroth tool for machine learning.

por Babak K Z

30 de nov. de 2020

very good and goal oriented cours, no loss of time , covers rapidly subjects that really increase students knowledge on python tools for data analysis. very interesting and useful cover on regression for tolls as well as explaining the statistical concept in a very simple way.

por Deleted A

26 de oct. de 2020


por federico b c

12 de may. de 2020

It's a great course. I enjoyed a lot. Easy to follow.

However I miss go deeper with the meaning of the numbers (for example the R2 each time we calculate it) and to get deeper insights of the data after having on the table many interesting number for the analysis.

Thanks for all.

por Lee D

29 de jun. de 2021

Everything is terrific! This course has in-depth lecturing while providing a great resource for practicing.

The only thing that bothered me is that there was a misleading ipynb url at the final project section. There were two different urls directing to two different projects.

por Veon G

5 de jun. de 2020

I have a specialist diploma with business analytic. However that was using software to do the visualization and analysis.

I guess it helps on my journey. I can relate the machine learning concept to this course.

This course is fantastic. Teaching you step by step progressively.

por Matt M

29 de jun. de 2020

Great overall experience. Although it would be great actually understanding the Python language in ways where you're actually learning about what each code means and does, I think this is more of an introductory course in terms of just understanding what Data Science is.